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Background NOAA’s Hazard Mapping System (HMS) smoke product comprises smoke plumes digitised from satellite imagery. Recent studies have used HMS as a proxy for surface smoke presence. Aims We compare HMS with airport observations, air quality station measurements and model estimates of near-surface smoke. Methods We quantify the agreement in numbers of smoke days and trends, regional discrepancies in levels of near-surface smoke fine particulate matter (PM2.5) within HMS polygons, and separation of total PM2.5 on smoke and non-smoke days across the contiguous US and Alaska from 2010 to 2021. Key results We find large overestimates in HMS-derived smoke days and trends if we include light smoke plumes in the HMS smoke day definition. Outside the western US and Alaska, near-surface smoke PM2.5 within areas of HMS smoke plumes is low and almost indistinguishable across density categories, likely indicating frequent smoke aloft. Conclusions Compared with airport, Environmental Protection Agency (EPA) and model-derived estimates, HMS most closely reflects surface smoke in the Pacific and Mountain regions and Alaska when smoke days are defined using only heavy plumes or both medium and heavy plumes. Implications We recommend careful consideration of biases in the HMS smoke product for air quality and public health assessments of fires.

Purpose Methods Results Conclusion Cataract, the leading cause of blindness worldwide, is a multifactorial disease involving oxidative stress mechanisms. The aim of our study was to investigate the relationship between air pollution exposure and the incidence of cataract surgery.The 3C‐Alienor study is a population‐based cohort of residents of Bordeaux, France, aged 65 years or more, recruited in 1999–2000 and followed every 2–3 years until 2017. Cataract surgery was self‐reported and checked at slit‐lamp by trained professionals. Average air pollution exposure (particulate matter ≤2.5 μm (PM2.5), black carbon (BC), nitrogen dioxide (NO2)) in the 10 years preceding baseline was estimated at the participants' geocoded residential address, using temporally adjusted land use regression. Associations of 10‐year average air pollution exposure with incidence of cataract were estimated using Cox proportional hazard models adjusted for confounders.The study included 829 subjects without cataract surgery prior to inclusion; the mean age at inclusion was 72.6 years (standard deviation (SD): 4.2) and 61% were women. The median (Interquartile‐range (IQR)) follow‐up duration was 14.1 (6.4) years during which 507 participants underwent cataract surgery. Exposure to a concentration ≥40 μg/m3 of NO2 (the current regulatory limit value in Europe) was associated with incident cataract surgery (HR = 1.46, CI (1.16, 1.84), p = 0.001). No statistically significant association was found with PM2.5 and BC.Long‐term exposure to a NO2 concentration ≥ 40 μg/m3 was associated with an increased incidence of cataract surgery. Complying with current European air pollution standards could reduce cataract surgery costs and improve population quality of life. [ABSTRACT FROM AUTHOR]

Linking meteorology and air pollutants is a key challenge. The study investigated meteorological effects on PM 2.5 concentration using the advanced convergent cross mapping method, utilizing hourly PM 2.5 concentration and six meteorological factors across eight provinces and cities in Vietnam. Results demonstrated that temperature (ρ = 0.30) and radiation (ρ = 0.30) produced the highest effects, followed by humidity (ρ = 0.28) and wind speed (ρ = 0.24), while pressure (ρ = 0.22) and wind direction (ρ = 0.17) produced the weakest effects on PM 2.5 concentration. Comparing the ρ values showed that temperature, wind speed, and wind direction had greater impacts on PM 2.5 concentration during the dry season whereas radiation had a more influence during the wet season; Southern stations experienced larger meteorological effects. Temperature, humidity, pressure, and wind direction had both positive and negative influences on PM 2.5 concentration, while radiation and wind speed mostly had negative influences. During PM 2.5 pollution episodes, there was more contribution of meteorological effects on PM 2.5 concentration indicated by ρ values. At contaminated levels, humidity (ρ = 0.45) was the most dominant factor affecting PM 2.5 concentration, followed by temperature (ρ = 0.41) and radiation (ρ = 0.40). Pollution episodes were pointed out to be more prevalent under higher humidity, higher pressure, lower temperature, lower radiation, and lower wind speed. The ρ calculation also revealed that lower temperature, lower radiation, and higher humidity greatly accelerated each other under pollution episodes, further enhancing PM 2.5 concentration. The findings contributed to the literature on meteorology and air pollution interaction. [ABSTRACT FROM AUTHOR]

There is a lack of evidence from cohort studies on the causal association of long‐term exposure to ambient fine particulate matter (PM2.5) and its chemical components with the risk of nasopharyngeal carcinoma (NPC) recurrence. Based on a 10‐year prospective cohort of 1184 newly diagnosed NPC patients, we comprehensively evaluated the potential causal links of ambient PM2.5 and its chemical components including black carbon (BC), organic matter (OM), sulfate (SO42−), nitrate (NO3−), and ammonium (NH4+) with the recurrence risk of NPC using a marginal structural Cox model adjusted with inverse probability weighting. We observed 291 NPC patients experiencing recurrence during the 10‐year follow‐up and estimated a 33% increased risk of NPC recurrence (hazard ratio [HR]: 1.33, 95% confidence interval [CI]: 1.02–1.74) following each interquartile range (IQR) increase in PM2.5 exposure. Each IQR increment in BC, NH4+, OM, NO3−, and SO42− was associated with HRs of 1.36 (95%CI: 1.13–1.65), 1.35 (95%CI: 1.07–1.70), 1.33 (95%CI: 1.11–1.59), 1.32 (95%CI: 1.06–1.64), 1.31 (95%CI: 1.08–1.57). The elderly, patients with no family history of cancer, no smoking history, no drinking history, and those with severe conditions may exhibit a greater likelihood of NPC recurrence following exposure to PM2.5 and its chemical components. Additionally, the effect estimates of the five components are greater among patients who were exposed to high concentration than in the full cohort of patients. Our study provides solid evidence for a potential relationship between long‐term exposure to PM2.5 and its components and the risk of NPC recurrence. [ABSTRACT FROM AUTHOR]

Despite the increased frequency with which wildfire smoke now blankets portions of world, the effects of smoke on wildlife, and birds in particular, are largely unknown. We used 2 decades of banding data from the San Francisco Bay Bird Observatory to investigate how fine particulate matter (PM2.5)—a major component and indicator of wildfire smoke—influenced capture rates and body condition of 21 passerine or near-passerine bird species. Across all study species, we found a negative effect of acute PM2.5 exposure and a positive effect of chronic PM2.5 exposure on avian capture rates. Together, these findings are indicative of decreased bird activity or local site removal during acute periods of wildfire smoke, but increased activity or site colonization under chronic smoke conditions. Importantly, we also observed a negative relationship between chronic PM2.5 exposure and body mass change in individuals with multiple captures per season. Our results indicate that wildfire smoke likely influences the health and behavior of birds, ultimately contributing to a shift in activity and body condition, with differential short-term versus long-term impacts. Although more research is needed on the mechanisms driving these observed changes in bird health and behavior, as well as validation of these relationships in more areas, our results suggest that wildfire smoke is a potentially frequent large-scale environmental stressor to birds that deserves increasing attention and recognition. [ABSTRACT FROM AUTHOR]

During the past decade, the air quality has been greatly improved in China since the implementation of the "Clean Air Act". However, haze events are still being reported in some regions of China, and the pollution mechanism remains unclear. In this study, we investigate the chemical characteristics of the pollution mechanism of the PM2.5 composition in Suzhou from October 18 to December 15, 2020. A notable declining trend in temperature was observed from 18 to 27 November, which indicates the seasonal transition from fall to the winter season. Four representative periods were identified based on meteorological parameters and the PM2.5 mass concentrations. The heavy pollution period had the typical characteristics of a relatively low temperature, a high relative humidity, and mass loadings of atmospheric pollutants; nitrate was the dominant contributor to the haze pollution during this period. The nitrate formation mechanism was driven by the planetary boundary layer dynamics. The potential source contribution function model (PSCF) showed that the major PM2.5 composition originated from the northwest direction of the sampling site. The aerosol liquid water content presented increasing trends with an increasing relative humidity. The pH was the highest during the heavy pollution period, which was influenced by the aerosol liquid water content and the mass loadings of NO3−, SO42−, NH4+, and Cl−. The comprehensive analysis in this paper could improve our understanding of the nitrate pollution mechanism and environmental effects in this region. [ABSTRACT FROM AUTHOR]

Background: Previous studies have primarily focused on the links between fine particulate matter (PM2.5) and bone health among the general population instead of PM2.5 components and the specific population. We aimed to investigate the associations between PM2.5 components and bone health among middle-aged and elderly women. Methods: A total of 748 middle-aged and elderly women were randomly sampled from 32 streets/villages in Hubei Province. The concentrations of ambient PM2.5 and its components were extracted across various residential areas from the Tracking Air Pollution in China (TAP) dataset. Bone mineral density measurements were obtained from dual-energy X-ray absorptiometry scans of study participants. Multivariable logistic and linear models were employed to assess the relationship between PM2.5 and its components and bone loss. Results: Per interquartile range (IQR) increase in nitrate (NO3−) and ammonium (NH4+) concentrations were associated with 1.65 [95% confidence intervals (CI): 1.13, 2.30] and 1.77 (95% CI: 1.26, 2.49) times higher odds of osteoporosis, respectively. Long-term exposure to sulfate (SO42−), NO3−, and NH4+ was negatively associated with T-scores and bone mineral density in L1-L4 lumbar vertebrae. In addition, the elderly, women who have experienced menarche after the age of 14, and postmenopausal women were more susceptible to the water-soluble inorganic salts of PM2.5. Conclusion: The study emphasizes the need for comprehensive policies addressing air quality, with a specific focus on vulnerable populations such as middle-aged and elderly women. Public health interventions aimed at reducing ambient PM2.5 concentrations and minimizing exposure to its harmful components are crucial in mitigating the adverse impact on skeletal health and improving the overall well-being of communities. [ABSTRACT FROM AUTHOR]

Despite the substantial evidence on the health effects of short-term exposure to ambient fine particles (PM2.5), including increasing studies focusing on those from wildland fire smoke, the impacts of long-term wildland fire smoke PM2.5 exposure remain unclear. We investigated the association between long-term exposure to wildland fire smoke PM2.5 and nonaccidental mortality and mortality from a wide range of specific causes in all 3,108 counties in the contiguous United States, 2007 to 2020. Controlling for nonsmoke PM2.5, air temperature, and unmeasured spatial and temporal confounders, we found a nonlinear association between 12-mo moving average concentration of smoke PM2.5 and monthly nonaccidental mortality rate. Relative to a month with the long-term smoke PM2.5 exposure below 0.1 µg/m³, nonaccidental mortality increased by 0.16 to 0.63 and 2.11 deaths per 100,000 people per month when the 12-mo moving average of PM2.5 concentration was of 0.1 to 5 and 5+ µg/m³, respectively. Cardiovascular, ischemic heart disease, digestive, endocrine, diabetes, mental, and chronic kidney disease mortality were all found to be associated with long-term wildland fire smoke PM2.5 exposure. Smoke PM2.5 contributed to approximately 11,415 nonaccidental deaths/y (95% CI: 6,754, 16,075) in the contiguous United States. Higher smoke PM2.5-related increases in mortality rates were found for people aged 65 and above. Positive interaction effects with extreme heat were also observed. Our study identified the detrimental effects of long-term exposure to wildland fire smoke PM2.5 on a wide range of mortality outcomes, underscoring the need for public health actions and communications that span the health risks of both short-and long-term exposure. [ABSTRACT FROM AUTHOR]

PM2.5 poses a serious threat to human life and health, so the accurate prediction of PM2.5 concentration is essential for controlling air pollution. However, previous studies lacked the generalization ability to predict high-dimensional PM2.5 concentration time series. Therefore, a new model for predicting PM2.5 concentration was proposed to address this in this paper. Firstly, the linear rectification function with leakage (LeakyRelu) was used to replace the activation function in the Temporal Convolutional Network (TCN) to better capture the dependence of feature data over long distances. Next, the residual structure, dilated rate, and feature-matching convolution position of the TCN were adjusted to improve the performance of the improved TCN (LR-TCN) and reduce the amount of computation. Finally, a new prediction model (GRU-LR-TCN) was established, which adaptively integrated the prediction of the fused Gated Recurrent Unit (GRU) and LR-TCN based on the inverse ratio of root mean square error (RMSE) weighting. The experimental results show that, for monitoring station #1001, LR-TCN increased the RMSE, mean absolute error (MAE), and determination coefficient (R2) by 12.9%, 11.3%, and 3.8%, respectively, compared with baselines. Compared with LR-TCN, GRU-LR-TCN improved the index symmetric mean absolute percentage error (SMAPE) by 7.1%. In addition, by comparing the estimation results with other models on other air quality datasets, all the indicators have advantages, and it is further demonstrated that the GRU-LR-TCN model exhibits superior generalization across various datasets, proving to be more efficient and applicable in predicting urban PM2.5 concentration. This can contribute to enhancing air quality and safeguarding public health. [ABSTRACT FROM AUTHOR]

The short-term adverse effects of ambient fine particulate matter (PM 2.5) and ozone (O 3) on anxiety disorders (ADs) remained inconclusive. We applied an individual-level time-stratified case-crossover study, which including 126,112 outpatient visits for ADs during 2019–2021 in Guangdong province, China, to investigate the association of short-term exposure to PM 2.5 and O 3 with outpatient visits for ADs, and estimate excess outpatient visits in South China. Daily residential air pollutant exposure assessments were performed by extracting grid data (spatial resolution: 1 km × 1 km) from validated datasets. We employed the conditional logistic regression model to quantify the associations and excess outpatient visits. The results of the single-pollutant models showed that each 10 μg/m3 increase of PM 2.5 and O 3 exposures was significantly associated with a 3.14 % (95 % confidence interval: 2.47 %, 3.81 %) and 0.88 % (0.49 %, 1.26 %) increase in odds of outpatient visits for ADs, respectively. These associations remained robust in 2-pollutant models. The proportion of outpatient visits attributable to PM 2.5 and O 3 exposures was up to 7.20 % and 8.93 %, respectively. Older adults appeared to be more susceptible to PM 2.5 exposure, especially in cool season, and subjects with recurrent outpatient visits were more susceptible to O 3 exposure. As our study subjects were from one single hospital in China, it should be cautious when generalizing our findings to other regions. Short-term exposure to ambient PM 2.5 and O 3 was significantly associated with a higher odds of outpatient visits for ADs, which can contribute to considerable excess outpatient visits. • Exposure to ambient PM 2.5 and O 3 was associated with an increased odds of outpatient visits for anxiety disorders. • PM 2.5 and O 3 exposures were attributable to considerable excess outpatient visits. • Older adults were more susceptible to PM 2.5 exposure, especially in cool season. • Subjects with recurrent outpatient visits were more susceptible to O 3 exposure. [ABSTRACT FROM AUTHOR]

We examined the association between walkability and blood lipids in a nationally representative sample of 29,649 participants aged 3–79 years who participated in the Canadian Health Measures Survey (CHMS) cycles 1 to 6. We focused on seven lipid biomarkers: apolipoprotein A (Apo A), apolipoprotein B (Apo B), triglycerides (TG), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), total cholesterol (TC), and TC/HDL. Cross-sectional associations were analyzed using generalized linear mixed models incorporating survey-specific sampling weights. An increase in the Canadian Active Living Environments Index, a measure of neighborhood walkability, equivalent to the magnitude of its interquartile range (IQR) was associated with the following percentage (95% confidence intervals (CI)) changes in lipids: decreased TG, -2.85 (-4.77, -0.93) and TC/HDL, -1.68 (-2.80, -0.56), and increased HDL, 1.68 (0.93, 2.42). Significant effects were largely restricted to adults (aged 17 to 79). In the younger age group there were no significant associations between walkability and lipids in the fully adjusted model. Significant associations were more frequently seen in females than males. For females, fully adjusted significant inverse associations were observed for TG, LDL, and TC/HDL, and there were positive associations with HDL and Apo A. Canadians living in more walkable neighborhoods have more favorable lipid profiles, suggesting that the built environment has the potential to influence the risk profile for cardiovascular health, especially among adults and females. Highlights: Blood lipids were measured in participants of the Canadian Health Measures Survey. Neighborhood walkability was measured by the Canadian Active Living Index. Increased walkability was associated with lower TG and TC/HDL and higher HDL. Favourable associations were more common in females. Increased walkability may improve cardiovascular risk profiles. [ABSTRACT FROM AUTHOR]

In this study, we examine and assess the potential impact of diesel engine age on the levels of fine particulate matter (PM2.5) in school buses. The concentration of air pollutants is influenced by several factors, including the technical characteristics of the bus and its engine, the type of fuel used, the length of the commute, the weather conditions, and the ambient air pollution. The behavior of the bus on the road, during the commute to and from school, is also important. This includes its position in traffic, the number of bus stops, boarding procedures, as well as the opening of doors and windows. Data were collected by accompanying a student during their commute to and from school, with bus commutes serving as the sampling unit. A semi-parametric regression was applied to assess the link between the PM2.5 concentration and the bus engine age. It was demonstrated that the bus engine age has a statistically significant positive correlation with the PM2.5 concentration inside the bus. The fine particulate matter concentrations during boarding at the school also depend on the engine age, indicating that bus idling affects the PM2.5 concentration. In the first two minutes before boarding in front of the school and the first two minutes inside the bus, the PM2.5 concentrations were 26.3 and 40.3 μg/m3, respectively. The findings of this study highlight the impact of bus engine age on the PM2.5 concentration, showing that the PM2.5 concentration increases with the engine age. However, the effect becomes less visible as the duration of the bus ride increases. [ABSTRACT FROM AUTHOR]

There is a growing need in public health to conduct large-scale epidemiological studies to investigate the health effects of fine particulate matter (PM2.5) exposure levels. In response to this need, we developed a real-time personal PM2.5 exposure monitoring system (PEPS: Personal Exposure PM2.5 System), which is capable of monitoring personal exposure concentration and uploading data in real time. The air quality self-labelling device, specifically customized for the PEPS, can be worn on the body and features functions for real-time data automatic upload, data storage, data export, and localization. This system enables researchers to obtain the big data of personal PM2.5 exposure concentration at low cost, with minimal manpower and technical requirements. It has been utilized to investigate the personal exposure levels of PM2.5 among college students in Beijing, China, providing a substantial volume of valuable data for indoor air quality and related epidemiological study. The maximum difference between the monitored daily average exposure concentration and the outdoor concentration was 265 µg/m3, corresponding to a relative error of 1579.5%. The correlation analysis of 11 factors showed that the correlation between exposure concentration and outdoor concentration was as high as 0.66 (p < 0.001), and the correlation between exposure concentration and other certain factors was in the range of [−0.11, −0.03]. [ABSTRACT FROM AUTHOR]

PM2.5 exposure is a challenging environmental issue that is closely related to cognitive development impairment; however, currently, relevant means for prevention and treatment remain lacking. Herein, we determined the preventive effect of docosahexaenoic acid (DHA) supplementation on the neurodevelopmental toxicity induced by PM2.5 exposure. Neonatal rats were divided randomly into three groups: control, PM2.5, and DHA + PM2.5 groups. DHA could ameliorate PM2.5-induced learning and memory dysfunction, as well as reverse the impairment of hippocampal synaptic plasticity, evidenced by enhanced long-term potentiation, recovered synaptic ultrastructure, and increased expression of synaptic proteins. Moreover, DHA increased CREB phosphorylation and BDNF levels and attenuated neuroinflammation and oxidative stress, reflected by lower levels of IBA-1, IL-1β, and IL-6 and increased levels of SOD1 and Nrf2. In summary, our findings demonstrated that supplementation of DHA effectively mitigated the cognitive dysfunction and synaptic plasticity impairment induced by early postnatal exposure to PM2.5. These beneficial effects may be attributed to the upregulation of the CREB/BDNF signaling pathway, as well as the reduction of neuroinflammation and oxidative stress. [ABSTRACT FROM AUTHOR]

Accumulating animal studies have demonstrated associations between ambient air pollution (AP) and metabolic dysfunction-associated fatty liver disease (MAFLD), but relevant epidemiological evidence is limited. We evaluated the association of long-term exposure to AP with the risk of incident MAFLD in Northwest China. The average AP concentration between baseline and follow-up was used to assess individual exposure levels. Cox proportional hazard models and restricted cubic spline functions (RCS) were used to estimate the association of PM2.5 and its constituents with the risk of MAFLD and the dose–response relationship. Quantile g-computation was used to assess the joint effects of mixed exposure to air pollutants on MAFLD and the weights of the various pollutants. We observed 1516 cases of new-onset MAFLD, with an incidence of 10.89%. Increased exposure to pollutants was significantly associated with increased odds of MAFLD, with hazard ratios (HRs) of 2.93 (95% CI: 1.22, 7.00), 2.86 (1.44, 5.66), 7.55 (3.39, 16.84), 4.83 (1.89, 12.38), 3.35 (1.35, 8.34), 1.89 (1.02, 1.62) for each interquartile range increase in PM2.5, SO42−, NO3−, NH4+, OM, and BC, respectively. Stratified analyses suggested that females, frequent exercisers and never-drinkers were more susceptible to MAFLD associated with ambient PM2.5 and its constituents. Mixed exposure to SO42−, NO3−, NH4+, OM and BC was associated with an increased risk of MAFLD, and the weight of BC had the strongest effect on MAFLD. Exposure to ambient PM2.5 and its constituents increased the risk of MAFLD. [ABSTRACT FROM AUTHOR]

BackgroundPrevious research on chlorinated paraffins (CPs) in fine particulate matter (PM2.5) has predominantly focused on short- and medium-chain chlorinated paraffins (SCCPs and MCCPs), and few studies could simultaneously determine short-, medium-, and long-chain chlorinated paraffins (LCCPs). Simultaneous extraction and determination of SCCPs, MCCPs, and LCCPs in PM2.5 could provide technical support for their environmental monitoring and human health risk assessment.ObjectiveTo establish a method based on QUEChERS pretreatment method in conjunction with ultra-performance liquid chromatography-quadrupole/orbitrap high resolution mass spectrometry for simultaneously determining the levels of SCCPs, MCCPs, and LCCPs in PM2.5. MethodsThe extraction solvents, extraction salts, and extraction steps of a QuEChERS method were optimized. The extraction efficiencies of the target substances were compared under 4 extraction solvents [acetonitrile, dichloromethane, and n-hexane solvents in sequence; acetonitrile: dichloromethane: n-hexane = 1: 1: 2 (v/v/v) mixed solvent; 1% acetic acid-acetonitrile: dichloromethane: n-hexane = 1: 1: 1 (v/v/v) mixed solvent; acetonitrile: dichloromethane: n-hexane = 1: 1: 1 (v/v/v) mixed solvent], 2 dehydrated salts (anhydrous MgSO4+NaCl and anhydrous Na2SO4+NaCl), 2 purification salts (C18 and PSA), and 4 vortex time (5, 7.5, 10, and 12.5 min) conditions. Then internal standard was utilized to estimate linear range and detection limit of the refined QuEChERS approach. ResultsThe linearities of SCCPs, MCCPs, and LCCPs were good in the range of 10~1000 ng·mL−1 with the correlation coefficients all greater than 0.96. The method detection limits (MDLs) ranged from 0.01 to 0.29 ng·m−3. The spiked recoveries of SCCPs, MCCPs, and LCCPs at the low, medium, and high concentrations were 77.38%-81.64%, 93.11%-99.78%, and 87.41%-101.39%, respectively, and the relative standard deviations (RSDs) were 2.90%-12.84%. This method was used to determine the CPs levels in 11 PM2.5 samples from Shijiazhuang. The positive rates of ∑SCCPs, ∑MCCPs, and ∑LCCPs were all 100%, the concentration ranges were 0.24-2.18 ng·m−3 (mean 0.84 ng·m−3), 0.17-1.67 ng·m−3 (mean 0.70 ng·m−3), and 0.01-0.16 ng·m−3 (mean 0.04 ng·m−3), respectively, and the percentages to ΣCPs were 52.95%, 44.39%, and 2.66%, respectively. ConclusionThe method established in this study is simple, time-saving, solvent saving, and can simultaneously detect SCCPs, MCCPs, and LCCPs in PM2.5, which is suitable for the determination of PM2.5 samples in large quantities, and can also provide a reference for the detection methods of other halogenated organic compounds in PM2.5.

Abstract We examined the association between walkability and blood lipids in a nationally representative sample of 29,649 participants aged 3–79 years who participated in the Canadian Health Measures Survey (CHMS) cycles 1 to 6. We focused on seven lipid biomarkers: apolipoprotein A (Apo A), apolipoprotein B (Apo B), triglycerides (TG), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), total cholesterol (TC), and TC/HDL. Cross-sectional associations were analyzed using generalized linear mixed models incorporating survey-specific sampling weights. An increase in the Canadian Active Living Environments Index, a measure of neighborhood walkability, equivalent to the magnitude of its interquartile range (IQR) was associated with the following percentage (95% confidence intervals (CI)) changes in lipids: decreased TG, -2.85 (-4.77, -0.93) and TC/HDL, -1.68 (-2.80, -0.56), and increased HDL, 1.68 (0.93, 2.42). Significant effects were largely restricted to adults (aged 17 to 79). In the younger age group there were no significant associations between walkability and lipids in the fully adjusted model. Significant associations were more frequently seen in females than males. For females, fully adjusted significant inverse associations were observed for TG, LDL, and TC/HDL, and there were positive associations with HDL and Apo A. Canadians living in more walkable neighborhoods have more favorable lipid profiles, suggesting that the built environment has the potential to influence the risk profile for cardiovascular health, especially among adults and females.

Abstract Background Despite the adverse effects of ambient fine particulate matter (PM2.5) on type 2 diabetes and the beneficial role of physical activity (PA), the influence of PM2.5 on the relationship between PA and type 2 diabetes remains unclear. Methods In this prospective study with 71,689 participants, PA was assessed by a questionnaire and was categorized into quartiles for volume and three groups for intensity. Long‐term PM2.5 exposure was calculated using 1‐km resolution satellite‐based PM2.5 estimates. PM2.5 exposure and PA's effect on type 2 diabetes were assessed by cohort‐stratified Cox proportional hazards models, individually and in combination. Results In 488,166 person‐years of follow‐up, 5487 incident type 2 diabetes cases were observed. The association between PA and type 2 diabetes was modified by PM2.5. Compared with the lowest quartile of PA volume, the highest quartile was associated with reduced type 2 diabetes risk in low PM2.5 stratification (≤65.02 µg/m3) other than in high PM2.5 stratification (>65.02 µg/m3), with the hazard ratio (HR) of 0.75 (95% confidence interval [CI]: 0.66–0.85) and 1.10 (95% CI: 0.99–1.22), respectively. Similar results were observed for PA intensity. High PM2.5 exposure combined with the highest PA levels increased the risk of type 2 diabetes the most (HR = 1.79, 95% CI: 1.59–2.01 for PA volume; HR = 1.82, 95% CI: 1.64–2.02 for PA intensity). Conclusion PA could reduce type 2 diabetes risk in low‐pollution areas, but high PM2.5 exposure may weaken or even reverse the protective effects of PA. Safety and health benefits of PA should be thoroughly assessed for long‐term polluted residents.

Previous research has suggested a correlation between fine particulate matter (PM2.5) and type 2 diabetes mellitus (T2DM). However, the causality was vulnerable to confounding variables. A two-sample multivariable mendelian randomization study was designed to examine the causal connection between PM2.5 and T2DM. PM2.5 trait was investigated as exposure while T2DM-related traits as outcomes. The summary data were obtained from the Finngen database and the open genome-wide association study database. The mendelian randomization estimates were obtained using the inverse-variance weighted approach, and multiple sensitivity analyses were conducted. There were potential causal relationships between PM2.5 and T2DM (OR = 2.418; P = 0.019), PM2.5 and glycated hemoglobin (HbA1c) (OR = 1.590; P = 0.041), and PM2.5 and insulin metabolism. PM2.5 was found to have no causal effect on fasting glucose and insulin, 2-h glucose, and insulin-like growth factor binding protein-1 (P > 0.05), while had a potential protective effect against some diabetes complications. Our findings indicated potential causal relationships among PM2.5 and T2DM, especially the causal relationship between PM2.5 and long-term glucose levels. [Display omitted] • PM2.5 exposure may act as a risk factor for developing T2DM and lead to abnormalities in glucose metabolism and insulin resistance. • PM2.5 exposure confers a potential protective effect of PM2.5 against certain T2DM complications • This article focused on T2DM and expanded the scope to include more T2DM-related indicators. [ABSTRACT FROM AUTHOR]

Purpose: To assess the correlation between the worldwide burden of vision impairment (VI) and fine particulate matter (PM) 2.5. Methods: In this retrospective cross-sectional study, global and national prevalence and disability-adjusted lost year (DALY) numbers and rates of total VI, glaucoma, cataract, and age-related macular degeneration (AMD) were obtained from the Global Burden of Disease database. The global and national levels of PM2.5 levels were also extracted. The main outcome measures were the correlation of PM2.5 levels with total VI and three ocular diseases in different age, sex, and socioeconomic subgroups. Results: In 2019, the worldwide prevalence of total VI and exposure level of PM2.5 was 9.6% (95% uncertainty interval: 8.0–11.3) and 42.5 μg/m3, respectively. The national age-standardized prevalence rates of total VI (rp = 0.52, P < 0.001), glaucoma (rp = 0.65, P < 0.001), AMD (rp = 0.67, P < 0.001), and cataract (rp = 0.44, P < 0.001) have a positive correlation with PM2.5 levels. In addition, the national age-standardized DALY rates of total VI (rp = 0.62, P < 0.001), glaucoma (rp = 0.62, P < 0.001), AMD (rp = 0.54, P < 0.001), and cataract (rp = 0.45, P < 0.001) significantly correlated with PM2.5 levels. The correlations remained significant in different age, sex, and sociodemographic subgroups. Conclusion: National prevalence rates of VI and three major ocular diseases correlate significantly with PM2.5 exposure levels, worldwide.

Abstract Background There is increasing evidence that exposure to PM2.5 and its constituents is associated with an increased risk of gestational diabetes mellitus (GDM), but studies on the relationship between exposure to PM2.5 constituents and the risk of GDM are still limited. Methods A total of 17,855 pregnant women in Guangzhou were recruited for this retrospective cohort study, and the time-varying average concentration method was used to estimate individual exposure to PM2.5 and its constituents during pregnancy. Logistic regression was used to assess the relationship between exposure to PM2.5 and its constituents and the risk of GDM, and the expected inflection point between exposure to PM2.5 and its constituents and the risk of GDM was estimated using logistic regression combined with restricted cubic spline curves. Stratified analyses and interaction tests were performed. Results After adjustment for confounders, exposure to PM2.5 and its constituents (NO3 −, NH4 +, and OM) was positively associated with the risk of GDM during pregnancy, especially when exposure to NO3 − and NH4 + occurred in the first to second trimester, with each interquartile range increase the risk of GDM by 20.2% (95% CI: 1.118–1.293) and 18.2% (95% CI. 1.107–1.263), respectively. The lowest inflection points between PM2.5, SO4 2−, NO3 −, NH4 +, OM, and BC concentrations and GDM risk throughout the gestation period were 18.96, 5.80, 3.22, 2.67, 4.77 and 0.97 µg/m3, respectively. In the first trimester, an age interaction effect between exposure to SO4 2−, OM, and BC and the risk of GDM was observed. Conclusions This study demonstrates a positive association between exposure to PM2.5 and its constituents and the risk of GDM. Specifically, exposure to NO3 −, NH4 +, and OM was particularly associated with an increased risk of GDM. The present study contributes to a better understanding of the effects of exposure to PM2.5 and its constituents on the risk of GDM.

ObjectiveTo explore the association between short-term exposure to atmospheric fine particulate matter （PM2.5） and ozone （O3） and systemic inflammatory indicators in patients with pneumonia， and to identify the susceptible populations.MethodsFrom September 2018 to April 2020， data of 1 480 patients admitted for pneumonia was collected from a tertiary hospital in Taiyuan City. Generalized additive models （GAMs） were used to explore the associations between PM2.5 and O3 exposure and inflammatory indicators of patients with pneumonia； and to explore the susceptibility factors and susceptible populations to PM2.5 and O3 exposures through stratified analyses.ResultsThe short-term exposure to PM2.5 was associated with changes in peripheral blood C-reation protein （CRP）， erythrocyte sedimentation （ESR）， easinophil （EOS）， neutrophil （NEU） and neutrophil-lymphocyte ratio （NLR） in patients with pneumonia， and there were different degrees of hysteresis effects， with the effect values reaching a maximum at lag03， lag03， lag0， lag03， lag03， respectively， which were 4.13% （95%CI： 0.43%‒7.84%）， 3.10% （95%CI： 0.24%‒5.97%）， 5.27% （95%CI： 3.12%‒7.42%）， 1.85% （95%CI： 0.36%‒3.34%）， and 2.53% （95%CI： 0.53%‒4.74%） for every 10 μg·m-3 of PM2.5. The changes in O3 concentration were associated with the elevation of peripheral blood PCT and ESR in patients with pneumonia， and their effect values all reached the maximum at lag01 d， every 1 μg·m-3 of O3 elevation increased by 0.38% （95%CI： 0.04%‒0.73%） and 0.47% （95%CI： 0.19%‒0.76%）， respectively. Stratified analyses showed that the associations of PM2.5 with peripheral blood CRP， ESR， NEU， and NLR in pneumonia patients were more significant in males， the elderly， and those with onset in the cold season； the associations of O3 with peripheral blood PCT and ESR in pneumonia patients were more significant in the elderly and those with onset in the warm season， and the peripheral blood CRP and PCT in female patients with pneumonia were more susceptible to the changes of O3.ConclusionShort-term exposure to atmospheric PM2.5 and O3 are positively associated with changes in inflammatory indicators in patients with pneumonia， and the effects of PM2.5 on patients with pneumonia are more extensive than those of O3， with a longer lag effect. In addition， elderly patients with pneumonia are more sensitive to air pollution， male patients with pneumonia are more sensitive to PM2.5， and female patients with pneumonia are more sensitive to O3. Cold and warm seasons can exacerbate the effects of PM2.5 and O3 on inflammatory indicators in patients with pneumonia， respectively， and the patients must be protected well.

BackgroundImproper settings of outdoor smoking points in public places may increase the risk of secondhand smoke exposure among the population. Conducting research on air pollution in and around smoking spots and related influencing factors can provide valuable insights for optimizing the setting of outdoor smoking points. ObjectiveTo investigate the influence of the number of smokers at outdoor smoking points and the distance on the diffusion characteristics of surrounding air pollutants, in order to optimize the setting of outdoor smoking points. MethodsSurrounding the exhibition halls in the China International Import Expo (CIIE), two outdoor smoking points were randomly selected, one on the first floor (ground level) and the other on the second floor (16 m above ground), respectively. At 0, 3, 6, and 9 m from the smoking points in the same direction, validated portable air pollutant monitors were used to measure the real-time fine particulate matter (PM2.5) and carbon dioxide (CO2) concentrations for consecutive 5 d during the exhibition, as well as the environmental meteorological factors at 0 m with weather meters including wind speed, wind direction, and air pressure. An open outdoor atmospheric background sampling point was selected on each of the two floors to carry out parallel sampling. Simultaneously, the number of smokers at each smoking point were double recorded per minute. The relationships between the number of smokers, distance from the smoking points, and ambient PM2.5 and CO2 concentrations were evaluated by generalized additive regression models for time-series data after adjustment of confounders such as temperature, relative humidity, and wind speed. ResultsThe median numbers of smokers at smoking points on the first and second floors were 6 [interquartile range (IQR): 3, 9] and 9 (IQR: 6, 13), respectively. Windless (wind speed

Background: There is increasing evidence that exposure to PM2.5 and its constituents is associated with an increased risk of gestational diabetes mellitus (GDM), but studies on the relationship between exposure to PM2.5 constituents and the risk of GDM are still limited. Methods: A total of 17,855 pregnant women in Guangzhou were recruited for this retrospective cohort study, and the time-varying average concentration method was used to estimate individual exposure to PM2.5 and its constituents during pregnancy. Logistic regression was used to assess the relationship between exposure to PM2.5 and its constituents and the risk of GDM, and the expected inflection point between exposure to PM2.5 and its constituents and the risk of GDM was estimated using logistic regression combined with restricted cubic spline curves. Stratified analyses and interaction tests were performed. Results: After adjustment for confounders, exposure to PM2.5 and its constituents (NO3−, NH4+, and OM) was positively associated with the risk of GDM during pregnancy, especially when exposure to NO3− and NH4+ occurred in the first to second trimester, with each interquartile range increase the risk of GDM by 20.2% (95% CI: 1.118–1.293) and 18.2% (95% CI. 1.107–1.263), respectively. The lowest inflection points between PM2.5, SO42−, NO3−, NH4+, OM, and BC concentrations and GDM risk throughout the gestation period were 18.96, 5.80, 3.22, 2.67, 4.77 and 0.97 µg/m3, respectively. In the first trimester, an age interaction effect between exposure to SO42−, OM, and BC and the risk of GDM was observed. Conclusions: This study demonstrates a positive association between exposure to PM2.5 and its constituents and the risk of GDM. Specifically, exposure to NO3−, NH4+, and OM was particularly associated with an increased risk of GDM. The present study contributes to a better understanding of the effects of exposure to PM2.5 and its constituents on the risk of GDM. [ABSTRACT FROM AUTHOR]

High-cholesterol diet (HCD) and fine particulate matter (PM2.5) are related to stroke. However, little is known about the combined effects of stroke, especially for females. This study investigated the brain injuries in Apolipoprotein E−/− (ApoE−/−) female mice exposed to HCD plus PM2.5 for 6 months. The protein levels of the genes related to stroke and the blood–brain barrier (BBB) in different groups of mice were measured. The molecular regulation mechanisms were explored. The results showed that HCD and PM2.5 co-exposure altered brain–body weight ratio, behavior, brain pathology, and inflammatory markers in mice relative to exposure to HCD or PM2.5 alone. Co-exposure significantly changed the expressions of HIF-1α and the key genes in its signaling pathway in the brains of mice compared to the single exposure. It suggests that the HIF-1α pathway exerts an important regulatory role in brain injury and behavioral abnormality in female mice after 6-month exposure to HCD plus PM2.5, which are potential mechanisms for HCD and PM2.5-triggering stroke in female individuals. [ABSTRACT FROM AUTHOR]

Ambient particulate matter (PM2.5) is a potential risk factor for metabolic damage to the liver. Epidemiological studies suggest that elevated PM2.5 concentrations cause changes in hepatic metabolism, but there is a lack of laboratory evidence. Here, we aimed to evaluate the effects of PM2.5 exposure on liver metabolism in C57BL/6j female mice (10 months old) and to explore the mechanisms underlying metabolic alterations and differential gene expressions by combining metabolomics and transcriptomics analyses. The metabolomics results showed that PM2.5 exposure notably affected the metabolism of amino acids and organic acids and caused hepatic lipid and bile acid accumulation. The transcriptomic analyses revealed that PM2.5 exposure led to a series of metabolic pathway abnormalities, including steroid biosynthesis, steroid hormone biosynthesis, primary bile acid biosynthesis, etc. Among them, the changes in the bile acid pathway might be one of the causes of liver damage in mice. In conclusion, this study clarified the changes in liver metabolism in mice caused by PM2.5 exposure through combined transcriptomic and metabolomic analyses, revealed that abnormal bile acid metabolism is the key regulatory mechanism leading to metabolic-associated fatty liver disease (MAFLD) in mice, and provided laboratory evidence for further clarifying the effects of PM2.5 on body metabolism. [ABSTRACT FROM AUTHOR]

Accurate long-term PM2.5 prediction is crucial for environmental management and public health. However, previous studies have mainly focused on short-term air quality point predictions, neglecting the importance of accurately predicting the long-term trends of PM2.5 and studying the uncertainty of PM2.5 concentration changes. The traditional approaches have limitations in capturing nonlinear relationships and complex dynamic patterns in time series, and they often overlook the credibility of prediction results in practical applications. Therefore, there is still much room for improvement in long-term prediction of PM2.5. This study proposes a novel long-term point and interval prediction framework for urban air quality based on multi-source spatial and temporal data, which further quantifies the uncertainty and volatility of the prediction based on the accurate PM2.5 point prediction. In this model, firstly, multi-source datasets from multiple monitoring stations are preprocessed. Subsequently, spatial clustering of stations based on POI data is performed to filter out strongly correlated stations, and feature selection is performed to eliminate redundant features. In this paper, the ConvFormer-KDE model is presented, whereby local patterns and short-term dependencies among multivariate variables are mined through a convolutional neural network (CNN), long-term dependencies among time-series data are extracted using the Transformer model, and a direct multi-output strategy is employed to realize the long-term point prediction of PM2.5 concentration. KDE is utilized to derive prediction intervals for PM2.5 concentration at confidence levels of 85%, 90%, and 95%, respectively, reflecting the uncertainty inherent in long-term trends of PM2.5. The performance of ConvFormer-KDE was compared with a list of advanced models. Experimental results showed that ConvFormer-KDE outperformed baseline models in long-term point- and interval-prediction tasks for PM2.5. The ConvFormer-KDE can provide a valuable early warning basis for future PM2.5 changes from the aspects of point and interval prediction. [ABSTRACT FROM AUTHOR]

Air purifier use, shift work, and long-term exposure to fine particulate matter (PM2.5) are linked to platelet abnormality. However, the role of air purifier use and shift work in the individual or joint associations of PM2.5 and its components with platelet indices are largely unknown. A total of 8772 participants were recruited from a population of subway workers in China. PM2.5 and its component data were obtained from the Tracking Air Pollution in China dataset. The role of air purifier use and shift work in the association between PM2.5 and its components and platelet indices were analyzed. Among shift workers without air purifier use, positive associations of PM2.5 and each component in PM2.5 with the mean platelet volume (MPV) or platelet counts (PLT) were observed, whereas negative associations of PM2.5 and each component in PM2.5 with the platelet distribution width (PDW) were observed. Furthermore, estimated changes (95%CIs) in PLT, MPV, and PDW in response to each 10th percentile increment in the mixture of PM2.5 and its components were 0.8657 (0.2496, 1.4819), 0.0192 (0.0054, 0.0329), and −0.0648 (−0.0945, −0.0351), respectively, and sulfate in PM2.5 was the major contributor to those associations. Long-term exposure to PM2.5 and its components was related to increased platelet disorders among shift workers without air purifier use, and those associations were mainly attributed to sulfate in PM2.5. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM2.5) is a risk factor of cardiovascular disease. Associations between PM2.5 compositions and cardiovascular disease are a point of special interest but inconsistent. This study aimed to explore the cardiovascular effects of heavy metal(loid) compositions in PM2.5. Data for mortality, air pollutants and meteorological factors in Anyang, China from 2017 to 2021 were collected. Heavy metal(loid) in PM2.5 were monitored and examined monthly. A Case-crossover design was applied to the estimated data set. The interquartile range increase in cadmium (Cd), antimony (Sb) and arsenic (As) at lag 1 was associated with increment of 8.1% (95% CI: 3.3, 13.2), 4.8% (95% CI: 0.2, 9.5) and 3.5% (95% CI: 1.1, 6.0) cardiovascular mortality. Selenium in lag 2 was inversely associated with cerebrovascular mortality (RR = 0.920 95% CI: 0.862, 0.983). Current-day exposure of aluminum was positively associated with mortality from ischemic heart disease (RR = 1.083 95% CI: 1.001, 1.172). Stratified analysis indicated sex, age and season modified the cardiovascular effects of As (P < 0.05). Our study reveals that heavy metal(loid) play key roles in adverse effects of PM2.5. Cd, Sb and As were significant risk factors of cardiovascular mortality. These findings have potential implications for accurate air pollutants control and management to improve public health benefits. [ABSTRACT FROM AUTHOR]

The present study was conducted to address four key questions: (i) What are the levels of submicron particulate matter at the study area?, (ii) which are the major contributing sources of these particles?, and (iii) is there any seasonal changes in the levels of pollutants at the study site? Thus, the study was conducted at an urban residential site of Jaipur City, India, to determine the elemental and ionic composition of toxic elements associated with PM1 using inductively coupled plasma optical emission spectroscopy and ion chromatography to reveal specific sources. Monitoring was done for a period of 8 months between October 2020 and May 2021 considering three seasons: winter (December–February), pre‐monsoon (March–May), and post‐monsoon (October–November). PM1 samples were found to be highly enriched with Ag, Cd, B, Ni, and Zn. PM1 mass concentrations were observed to be greater in winter (104.13 ± 30.16 µg m−3) and lower in the pre‐monsoon season (83.62 ± 19.40 µg m−3). Ion concentrations (Cl−, NO32−, and SO42−) followed a similar pattern to PM1 concentrations. Source apportionment by positive matrix factorization at the study site revealed six major sources of pollutants (soil dust, agro‐based industry, automobile industry, salt aerosols, industrial activities, and biomass burning). [ABSTRACT FROM AUTHOR]

In this study, we describe the development of seasonal winter and summer (heating and non-heating season) land use regression (LUR) models for PM2.5 mass concentration for the city of Novi Sad, Serbia. The PM2.5 data were obtained through an extensive seasonal measurement campaign conducted at 21 locations in urban, urban/industrial, industrial and background areas in the period from February 2020–July 2021. At each location, PM2.5 samples were collected on quartz fibre filters for 10 days per season using a reference gravimetric pump. The developed heating season model had two predictors, the first can be associated with domestic heating over a larger area and the second with local traffic. These predictors contributed to the adjusted R2 of 0.33 and 0.55, respectively. The developed non-heating season model had one predictor which can be associated with local traffic, which contributed to the adjusted R2 of 0.40. Leave-one-out cross-validation determined RMSE/mean absolute error for the heating and non-heating season model were 4.04/4.80 μg/m3 and 2.80/3.17 μg/m3, respectively. For purposes of completeness, developed LUR models were also compared to a simple linear model which utilizes satellite aerosol optical depth data for PM2.5 estimation, and showed superior performance. The developed LUR models can help with quantification of differences between seasonal levels of air pollution, and, consequently, air pollution exposure and association between seasonal long-term exposure and possible health risk implications. [ABSTRACT FROM AUTHOR]

Airborne fine particulate matter (PM2.5) in air pollution has become a significant global public health concern related to allergic diseases. Previous research indicates that PM2.5 not only affects the respiratory system but may also induce systemic inflammation in various tissues. Moreover, its impact may vary among different populations, with potential consequences during pregnancy and in newborns. However, the precise mechanisms through which PM2.5 induces inflammatory reactions remain unclear. This study aims to explore potential pathways of inflammatory responses induced by PM2.5 through animal models and zebrafish embryo experiments. In this study, zebrafish embryo experiments were conducted to analyze the effects of PM2.5 on embryo development and survival, and mouse experimental models were employed to assess the impact of PM2.5 stimulation on various aspects of mice. Wild-type zebrafish embryos were exposed to a PM2.5 environment of 25–400 μg/mL starting at 6 h after fertilization (6 hpf). At 6 days post-fertilization, the survival rates of the 25, 50, 100, and 200 µg/mL groups were 100%, 80, 40%, and 40%, respectively. Zebrafish embryos stimulated with 25 μg/mL of PM2.5 still exhibited successful development and hatching. Additionally, zebrafish subjected to doses of 25–200 μg/mL displayed abnormalities such as spinal curvature and internal swelling after hatching, indicating a significant impact of PM2.5 stimulation on embryo development. In the mouse model, mice exposed to PM2.5 exhibited apparent respiratory overreaction, infiltration of inflammatory cells into the lungs, elevated levels of inflammatory response-related cytokines, and inflammation in various organs, including the liver, lungs, and uterus. Blood tests on experimental mice revealed increased expression of inflammatory and chemotactic cytokines, and GSEA indicated the induction of various inflammatory responses and an upregulation of the TNF-α/NFκB pathway by PM2.5. Our results provide insights into the harmful effects of PM2.5 on embryos and organs. The induced inflammatory responses by PM2.5 may be mediated through the TNF-α/NFκB pathway, leading to systemic organ inflammation. However, whether PM2.5-induced inflammatory responses in various organs and abnormal embryo development are generated through different pathways requires further study to comprehensively clarify and identify potential treatment and prevention methods. [ABSTRACT FROM AUTHOR]

Background Model-estimated air pollution exposure products have been widely used in epidemiological studies to assess the health risks of particulate matter with diameters of ≤2.5 µm (PM2.5). However, few studies have assessed the disparities in health effects between model-estimated and station-observed PM2.5 exposures. Methods We collected daily all-cause, respiratory and cardiovascular mortality data in 347 cities across 15 countries and regions worldwide based on the Multi-City Multi-Country collaborative research network. The station-observed PM2.5 data were obtained from official monitoring stations. The model-estimated global PM2.5 product was developed using a machine-learning approach. The associations between daily exposure to PM2.5 and mortality were evaluated using a two-stage analytical approach. Results We included 15.8 million all-cause, 1.5 million respiratory and 4.5 million cardiovascular deaths from 2000 to 2018. Short-term exposure to PM2.5 was associated with a relative risk increase (RRI) of mortality from both station-observed and model-estimated exposures. Every 10-μg/m3 increase in the 2-day moving average PM2.5 was associated with overall RRIs of 0.67% (95% CI: 0.49 to 0.85), 0.68% (95% CI: –0.03 to 1.39) and 0.45% (95% CI: 0.08 to 0.82) for all-cause, respiratory, and cardiovascular mortality based on station-observed PM2.5 and RRIs of 0.87% (95% CI: 0.68 to 1.06), 0.81% (95% CI: 0.08 to 1.55) and 0.71% (95% CI: 0.32 to 1.09) based on model-estimated exposure, respectively. Conclusions Mortality risks associated with daily PM2.5 exposure were consistent for both station-observed and model-estimated exposures, suggesting the reliability and potential applicability of the global PM2.5 product in epidemiological studies. [ABSTRACT FROM AUTHOR]

Worsening wildfire seasons in recent years are reversing decadal progress on the reduction of harmful air pollutants in the US, particularly in Western states. Measurements of the contributions of wildfire smoke to ambient air pollutants, such as fine particulate matter (PM2.5), at fine resolution scales would be valuable to public health research on climate vulnerable populations and compound climate risks. We estimate the influence of wildfire smoke emissions on daily PM2.5 at fine-resolution, 3 km, for California 2011–2020, using a geostatistical modeled ambient PM2.5 estimate and wildfire smoke plume data from NOAA Hazard Mapping System. Additionally, we compare this product with the US Environmental Protection Agency (EPA) daily and annual standards for PM2.5 exposure. Our results show wildfires significantly influence PM2.5 in California and nearly all exceedances of the daily US EPA PM2.5 standard were influenced by wildfire smoke, while annual exceedances were increasingly attributed to wildfire smoke influence in recent years. This wildfire-influenced PM2.5 product can be applied to public health research to better understand source-specific air pollution impacts and assess the combination of multiple climate hazard risks. [ABSTRACT FROM AUTHOR]

Based on the ambient air quality monitoring data of Xi′an from September to November in 2021,the pollution characteristics of regional PM2. 5 in Xi′an before, during and after the 14th National Games of the People′s Republic of China ＆ the National Games for Persons with Disabilities were analysed. In addition, the air mass transport pathways, potential source areas and their contributions to PM2. 5 mass concentrations were also determined by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, potential source contributing factor (PSCF) method and weighted concentration trajectory (CWT) method. The results showed that during the observation, Southeasterly winds dominated in Xi′an, and the PM2. 5 concentration was lowest during the 14th National Games of the People′s Republic of China (NG) and highest after the end of the National Games for Persons with Disabilities (PG）. The air mass transport pathways of PM2. 5 were dominated by the local transport near Southern Shaanxi, the proximity transport in the Easterly and Southerly directions, and the long-range transport in the Northwesterly direction. Potential source regions of PM2. 5 were mainly located in the cities and areas of Henan, Hubei, Guizhou, Sichuan, Chongqing, Xinjiang Uygur Autonomous Regions, Inner Mongolia Autonomous Region, Southern Shaanxi, and the junction of cities in Southern Shaanxi and neighboring provinces. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM2.5) increases the risks of lung cancer. Epigenetics provides a new toxicology mechanism for the adverse health effects of PM2.5. However, the regulating mechanisms of PM2.5 exposure on candidate gene DNA methylation changes in the development of lung cancer remain unclear. Abnormal expression of the glutathione S transferase (GST) gene is associated with cancer. However, the relationship between PM2.5 and DNA methylation-mediated GST gene expression is not well understood. In this study, we performed GST DNA methylation analysis and GST-related gene expression in human A549 cells exposed to PM2.5 (0, 50, 100 µg/mL, from Taiyuan, China) for 24 h (n = 4). We found that PM2.5 may cause DNA oxidative damage to cells and the elevation of GSTP1 promotes cell resistance to reactive oxygen species (ROS). The Kelch-1ike ECH-associated protein l (Keap1)/nuclear factor NF-E2-related factor 2 (Nrf2) pathway activates the GSTP1. The decrease in the DNA methylation level of the GSTP1 gene enhances GSTP1 expression. GST DNA methylation is associated with reduced levels of 5-methylcytosine (5mC), DNA methyltransferase 1 (DNMT1), and histone deacetylases 3 (HDAC3). The GSTM1 was not sensitive to PM2.5 stimulation. Our findings suggest that PM2.5 activates GSTP1 to defend PM2.5-induced ROS and 8-hydroxy-deoxyguanosine (8-OHdG) formation through the Keap1/Nrf2 signaling pathway and GSTP1 DNA methylation. [ABSTRACT FROM AUTHOR]

[Display omitted] • We conducted spatial analysis around Yangtze and Yellow River basins. • Panel data for 20 years studied (11 provinces of Yangtze River and 9 provinces of Yellow river) • Major positive spatial autocorrelation was shown for climate pollution. • Both socio-economic and energy factors affect positive/ negatively to fine particulate matter. • Promotion of provincial coordination for monitoring is necessary to further reduce air pollution. The Yellow River Basin (YRB) and Yangtze River Basin (YZRB) stand as pivotal regions in China, holding paramount importance in both economic development and environmental security. However, the rapid pace of climate change and extensive human activities have dramatically reshaped these areas, leading to substantial alterations in natural landscapes and urban ecosystems. To ensure sustainable socio-economic growth, a profound understanding of the intricate interplay between socioeconomic factors and the emission of fine particulate matter (FPM) is imperative, along with an exploration of the underlying mechanisms governing these relationships. n this comprehensive study, we conducted spatial autocorrelation and spatial panel regression analyses, leveraging panel data encompassing the years from 2002 to 2021, derived from provincial-level administrative units within the YZRB and YRB. By adopting a holistic approach that considers comprehensive features and spatial effects, our research contributes substantively to the existing literature concerning the YZRB and YRB areas. Our analysis unveiled a notable decline in pollutant emissions over the course of the study period, yet it became evident that socioeconomic and energy-related factors continued to exert significant influence on FPM levels. Furthermore, we identified pronounced positive spatial autocorrelations in FPM emissions, suggesting a need for regionally tailored environmental management strategies. Employing various statistical tests, we rigorously examined the spatial autocorrelation patterns among the regions. Results from our random effect regression model and Geographically Weighted Regression (GWR) approach underscored the significant impact of socioeconomic and natural factors on FPM concentrations. Importantly, the magnitudes of these impacts exhibited variations contingent upon the specific river basin type. Within the YZRB, our findings emphasize the relevance of urbanization metrics, such as urban population, urban green space, Gross Domestic Product (GDP), and economic spending, which displayed positive and statistically significant relationships with FPM concentrations. Conversely, in the YRB, the utilization of energy resources and natural assets emerged as pivotal determinants. [ABSTRACT FROM AUTHOR]

Maternal exposure to air pollution during pregnancy has a substantial public health impact. Epidemiological evidence supports an association between maternal exposure to air pollution and low birth weight. A popular method to estimate this association while identifying windows of susceptibility is a distributed lag model (DLM), which regresses an outcome onto exposure history observed at multiple time points. However, the standard DLM framework does not allow for modification of the association between repeated measures of exposure and the outcome. We propose a distributed lag interaction model that allows modification of the exposure‐time‐response associations across individuals by including an interaction between a continuous modifying variable and the exposure history. Our model framework is an extension of a standard DLM that uses a cross‐basis, or bi‐dimensional function space, to simultaneously describe both the modification of the exposure‐response relationship and the temporal structure of the exposure data. Through simulations, we showed that our model with penalization out‐performs a standard DLM when the true exposure‐time‐response associations vary by a continuous variable. Using a Colorado, USA birth cohort, we estimated the association between birth weight and ambient fine particulate matter air pollution modified by an area‐level metric of health and social adversities from Colorado EnviroScreen. [ABSTRACT FROM AUTHOR]

With the rapid expansion of industrial scale, an increasing number of fine particulate matter (PM2.5) has bringing health concerns. Although exposure to PM2.5 has been clearly associated with male reproductive toxicity, the exact mechanisms are still unclear. Recent studies demonstrated that exposure to PM2.5 can disturb spermatogenesis through destroying the blood-testis barrier (BTB), consisting of different junction types, containing tight junctions (TJs), gap junctions (GJs), ectoplasmic specialization (ES) and desmosomes. The BTB is one of the tightest blood-tissue barriers among mammals, which isolating germ cells from hazardous substances and immune cell infiltration during spermatogenesis. Therefore, once the BTB is destroyed, hazardous substances and immune cells will enter seminiferous tubule and cause adversely reproductive effects. In addition, PM2.5 also has shown to cause cells and tissues injury via inducing autophagy, inflammation, sex hormones disorder, and oxidative stress. However, the exact mechanisms of the disruption of the BTB, induced by PM2.5, are still unclear. It is suggested that more research is required to identify the potential mechanisms. In this review, we aim to understand the adverse effects on the BTB after exposure to PM2.5 and explore its potential mechanisms, which provides novel insight into accounting for PM2.5-induced BTB injury. [ABSTRACT FROM AUTHOR]

The effects of PM2.5 on human health fluctuate greatly among various age groups, influenced by a range of physiological and immunological reactions. This paper compares the pathogenesis of the disease caused by PM2.5 in people of different ages, focusing on how children, adults, and the elderly are each susceptible to it because of differences in their bodies. Regarding children, exposure to PM2.5 is linked to many negative consequences. These factors consist of inflammation, oxidative stress, and respiratory problems, which might worsen pre-existing conditions and potentially cause neurotoxicity and developmental issues. Epigenetic changes can affect the immune system and make people more likely to get respiratory diseases. On the other hand, exposures during pregnancy can change how the cardiovascular and central nervous systems develop. In adults, the inhalation of PM2.5 is associated with a wide range of health problems. These include respiratory difficulties, reduced pulmonary function, and an increased susceptibility to illnesses such as asthma, chronic obstructive pulmonary disease (COPD), and lung cancer. In addition, exposure to PM2.5 induces systemic inflammation, cardiovascular diseases, insulin resistance, and neurotoxic consequences. Evident disturbances in the immune system and cognitive function demonstrate the broad impact of PM2.5. The elderly population is prone to developing respiratory and cardiovascular difficulties, which worsen their pre-existing health issues and raise the risk of cognitive decline and neurological illnesses. Having additional medical conditions, such as peptic ulcer disease, significantly increases the likelihood of being admitted to hospital. [ABSTRACT FROM AUTHOR]

Pyroptosis represents a type of cell death mechanism notable for its cell membrane disruption and the subsequent release of proinflammatory cytokines. The Nod-like receptor family pyrin domain containing inflammasome 3 (NLRP3) plays a critical role in the pyroptosis mechanism associated with various diseases resulting from particulate matter (PM) exposure. Tert-butylhydroquinone (tBHQ) is a synthetic antioxidant commonly used in a variety of foods and products. The aim of this study is to examine the potential of tBHQ as a therapeutic agent for managing sinonasal diseases induced by PM exposure. The occurrence of NLRP3 inflammasome-dependent pyroptosis in RPMI 2650 cells treated with PM < 4 µm in size was confirmed using Western blot analysis and enzyme-linked immunosorbent assay results for the pyroptosis metabolites IL-1β and IL-18. In addition, the inhibitory effect of tBHQ on PM-induced pyroptosis was confirmed using Western blot and immunofluorescence techniques. The inhibition of tBHQ-mediated pyroptosis was abolished upon nuclear factor erythroid 2-related factor 2 (Nrf2) knockdown, indicating its involvement in the antioxidant mechanism. tBHQ showed potential as a therapeutic agent for sinonasal diseases induced by PM because NLRP3 inflammasome activation was effectively suppressed via the Nrf2 pathway. [ABSTRACT FROM AUTHOR]

Air pollution is one of the major global public health challenges. Using annual fine particulate matter (PM2.5) concentration data from 2016 to 2021, along with the global exposure mortality model (GEMM), we estimated the multi-year PM2.5-pollution-related deaths divided by different age groups and diseases. Then, using the VSL (value of statistical life) method, we assessed corresponding economic losses and values. The number of deaths attributed to PM2.5 in Beijing in 2021 fell by 33.74 percent from 2016, while health economic losses would increase by USD 4.4 billion as per capita disposable income increases year by year. In 2021, the average annual concentration of PM2.5 in half of Beijing's municipal administrative districts is less than China's secondary ambient air quality standard (35 μg/m3), but it can still cause 48,969 deaths and corresponding health and economic losses of USD 16.31 billion, equivalent to 7.9 percent of Beijing's GDP. Therefore, it is suggested that more stringent local air quality standards should be designated to protect public health in Beijing. [ABSTRACT FROM AUTHOR]

Abstract Fine particulate matter (PM2.5) is suggested to pose a severe risk to the kidneys by inducing functional degradation and chronic kidney diseases (CKD). This study aims to explore the nephrotoxicity of PM2.5 exposure and the underlying mechanism. Herein, based on the UK Biobank, it is found that per interquartile range (IQR) increase in PM2.5 is associated with a 6% (95% CI: 1%–11%), 7% (95% CI: 3%–11%), 9% (95% CI: 4%–13%), 11% (95% CI: 9%–13%), and 10% (95% CI: 8%–12%) increase in the risk of nephritis, hydronephrosis, kidney stone, acute renal failure, and CKD, respectively. In experimental study, noticeable kidney injury, which is the initiation of kidney diseases, is observed with PM2.5 exposure in C57BL/6N mice (n = 8), accompanied with oxidative stress, autophagy and pyroptosis. In vitro, HK‐2 cells with PM2.5‐stimulation exhibit tubulopathy, increased reactive oxygen species (ROS) generation and activated pyroptosis and autophagy. All changes are abolished by ROS scavenger of N‐acetyl‐L‐cysteine (NAC) both in vivo and in vitro. In conclusion, the study provides evidence showing that PM2.5 exposure is associated with 5 kinds of kidney diseases by directly inducing nephrotoxicity, in which ROS may be the potential target by triggering autophagy and pyroptosis.

Background: Fine particulate matter (PM2.5) induces ocular surface toxicity through pyroptosis, oxidative stress, autophagy, and inflammatory responses. However, the precise molecular pathways through which PM2.5 causes corneal damage remain unclear. This study aims to investigate the underlying mechanisms by exposing human corneal epithelial cells (HCECs) to PM2.5. Methods: After the morphology and chemical composition analysis of the PM samples, we conducted both in vivo and in vitro experiments to investigate PM2.5-induced corneal epithelial damage. We assessed corneal barrier function in HCECs using transepithelial electrical resistance (TEER) assays. To explore the molecular mechanisms of PM2.5-induced corneal epithelial damage, we performed whole-transcriptome resequencing, quantitative RT-PCR, and western blotting in vitro. In addition, we analyzed mouse corneas exposed to concentrated ambient PM2.5 through immunofluorescence staining to observe the resulting changes in corneal epithelial protein expression in vivo. Results: Our results showed significant impairment of corneal epithelial barrier function in PM2.5-treated HCECs, as indicated by decreased TEER values. The expression of thrombospondin-1 (THBS1) and claudin-1, both key factors for maintaining corneal epithelial barrier integrity, was markedly reduced at the gene and protein levels in both in vitro and in vivo PM2.5 exposure models. Moreover, the levels of tight junction-associated proteins, including occludin, zonula occludens-1 (ZO-1) and ZO-2, essential components of the corneal epithelial barrier, were significantly diminished in PM2.5-treated HCECs. Conclusion: PM2.5 exposure leads to corneal epithelium damage by disrupting tight junction proteins and THBS1 expression. These findings provide insight into potential pathways for PM2.5-induced ocular toxicity and underscore the need for protective strategies against such environmental pollutants.

Stent(s) insertion is a common form of surgery for patients with cardiovascular diseases, and is associated with a high rate of hospital readmission. This study aims to investigate the acute association between PM2.5 exposure and hospital readmission for patients with cardiovascular disease and a history of stent(s) insertion. The records of hospital admission were collected from the Beijing Municipal Commission of Health and Family Planning Information Center between 1st January 2013 and 31st December 2017. Subsequent hospital readmission records for patients with a history of stent(s) insertion or without any surgery were extracted. The conditional logistic regression model was applied to investigate the association between PM2.5 concentration and cardiovascular disease readmission in patients who had undergone stent(s) insertion or without any surgery. A total of 81,468 patients who had a history of stent(s) insertion were included in this study. Of these, 17,224 patients (21.1 % of the total number of patients) were readmitted 27,749 times due to cardiovascular disease. The median daily PM2.5 concentration was 62.8 μg/m3 with an interquartile range (IQR) of 71.5 μg/m3. The excess risk (ER) associated 10 μg/m3 increase in PM2.5 concentration for readmission due to cardiovascular disease was 0.48 % (95 % CI: 0.09 %, 0.87 %) in patients with a history of stent(s) insertion. Patients who had stent(s) insertion at the vessel bifurcation site showed the highest risk of readmission for cardiovascular disease when exposed to PM2.5; the ER was 4.12 % (95 % CI: 1.60 %, 6.70 %). PM2.5 was significantly associated with angina pectoris and readmission for chronic ischemic heart disease in patients with a history of stent(s) insertion. PM2.5 had a significant association with cardiovascular readmission among patients with a history of insertion of stent(s). Patients who had vessel bifurcation treated showed the highest risk of readmission.

Background: The public health relevance of daily Air Quality Index (AQI) activity guidelines for the general adult public in the United States to prevent atherosclerotic cardiovascular disease (ASCVD) events is questionable. Objectives: The purpose of the study was to explore the utility of a policy tailoring activity guidance to calculated ASCVD risk rather than uniform recommendations to the general adult public as currently provided. Methods: We calculated the number needed to treat (NNT) to prevent one ASCVD event per day by following activity recommendations across 10-year ASCVD risk scores (1% to 20%). Second, we modeled the benefits of tailoring recommendations to ASCVD risk. Results: The NNT decreased as ASCVD risk and/or AQI levels increased. At AQIs up to 151 (68% of days with AQIs above moderate in the United States), the NNTs remained untenably high (>2.7-55.3 million) across ASCVD risk. Under unhealthy conditions (AQIs 151-200), 28% of elevated AQIs, NNTs

Background: China has implemented rigorous clean air policies since 2013 to address PM2.5 pollution particularly affecting economically developed regions. The Fusion relative risk model was recently developed to better capture the association between long-term PM2.5 exposure and mortality risk, but it has not been used in China. Methods: We estimated cause-specific PM2.5 attributable deaths among adults (≥ 25 years) across China over 2005–2020 at a 0.1° × 0.1° spatial resolution using the Fusion model, and also adopted the Global Exposure Mortality Model (GEMM) for comparison. We investigated 31 provinces and targeted five mega city clusters: Beijing–Tianjin–Hebei cluster (BTH), Yangtze River Delta cluster (YRD), Pearl River Delta cluster (PRD), Cheng–Yu cluster (CY) and Middle reaches of the Yangtze River cluster (MYR). Results: The Fusion model estimated PM2.5 attributable deaths increased from 2.38 million (95 % UI: 2.06-2.64) in 2005 to 2.68 million (95 % UI: 2.33-2.95) in 2013 (12.6 %), then declined by 11.6 % to 2.37 million (95 % UI: 2.04-2.65) in 2020. Ischemic Heart Disease (IHD) and Stroke contributed most to the total attributable deaths (33.4 % and 35.0 % in 2020). Compared with the GEMM, the Fusion model generated higher attributable mortality estimates for IHD, Stroke and Chronic Obstructive Pulmonary Disease, but lower estimates for Lung Cancer and Lower Respiratory Infections. PM2.5 attributable deaths were clustered in densely populated and highly polluted regions, with Henan and Shandong bearing the highest mortality burden among the 31 provinces. PM2.5 attributable deaths in BTH, YRD, PRD, CY and MYR declined by 5.3 %, 11.5 %, 18.0 %, 25.4 % and 18.6 % respectively over 2013–2020, with greater declines in attributable mortality rates (18.9 %, 23.8 %, 33.8 %, 27.3 % and 24.1 %). Conclusions: Future clean air policies in China should consider regional disparities and continue prioritizing highly polluted and densely populated urban areas, including the five mega city clusters.

Fine particulate matter (PM2.5) exposure has been extensively linked to reproductive and developmental dysfunctions, yet the underlying mechanisms remain elusive. This study employed single-cell RNA sequencing (scRNA-seq) to investigate PM2.5-induced changes in uterine cell populations and gene expression profiles in mice during estrus and early pregnancy. Methodologically, we intranasally inoculated mice with 20 μL of 4.0 mg/mL PM2.5 suspension during their estrus and early pregnancy periods. Utilizing scRNA-seq analysis, we revealed significant alterations in cell type composition following PM2.5 exposure. Notably, we observed a marked decrease in the proportion of natural killer (NK) cells in PM2.5-exposed mice (2.00 % vs. 8.97 % in controls). Further functional enrichment analysis identified suppression of the IL-17 signaling pathway in NK cells as a key mechanism of PM2.5-induced toxicity. GSEA analysis showed in-depth details of the downregulated genes in this pathway, including Fosb, S100a8, Tnfaip3, IL-17a, and S100a9. PM2.5 exposure also disrupted intercellular communication within the uterine microenvironment, with the number of cell interactions decreasing from 483 to 315 and interaction strength reducing from 12.43 to 6.78 compared to controls. Histological examination revealed that PM2.5 exposure led to thinning of the endometrium and less prominent main branches in uterine tissues, and immunofluorescence assays corroborated the altered expression of IL-17 pathway components, showing enhanced Hsp90ab1 expression and reduced FOSB, S100A8, and S100A9 expression in PM2.5-exposed uterine tissues. These findings provide novel insights into the cellular mechanisms of PM2.5-induced reproductive toxicity, highlighting the IL-17 signaling pathway in uterine NK cells as a potential target for therapeutic interventions. Our results underscore the need for air quality regulations and open new avenues for developing biomarkers and targeted therapies to mitigate the reproductive risks associated with PM2.5 exposure.

Background: Fine particulate matter (PM2.5) exposure is an important environmental risk for maternal and children's health, with peak exposures especially those derived from primary combustion hypothesized to pose greater risk. Identifying PM2.5 peaks and their contributions to personal exposure remains challenging. This study measured personal PM2.5 exposure, characterized primary combustion peaks, and investigated their determinants during and after pregnancy and among Hispanic women in Los Angeles, CA. Methods: Continuous personal PM2.5 exposure, Global Positioning System geolocation, and ecological momentary assessment surveys were collected from 63 women for 4 consecutive days in their 1st trimester, 3rd trimester and 4–6 months postpartum. Based on the shape of PM2.5 time-series, primary combustion peaks were identified, characterized (number, duration, area under the curve [AUC]), and linked with locations they occurred in. Zero-inflated generalized mixed-effect models were used to examine the spatial and temporal determinants of PM2.5 peak exposures. Results: A total of 490 PM2.5 peaks were identified from 618 person-days of monitoring. Spending an additional minute at parks and open spaces was related to smaller (AUC decreased 3.1 %, 95 % CI: 1.5 %–4.6 %) and shorter (duration decreased 1.7 %, 0.5 %–2.9 %) PM2.5 peak exposure. An additional minute in vehicular trips also related to smaller and shorter peak exposure (AUC and duration decreased 2.5 %, 1.2 %–3.7 % and 1.8 %, 1.0 %–2.6 %, respectively). However, an additional minute at industrial locations was associated with greater number (3.6 %, 2.0 %–5.2 %), AUC (1.6 %, 0.1 %–3.2 %) and duration (1.0 %, 0.0 %–2.1 %) of personal PM2.5 peak exposure. Conclusions: This study demonstrates the potential to statistically identify exposure to primary combustion PM2.5 peaks and understand their determinants from personal monitoring data. Results suggest that visits to parks and open spaces may minimize PM2.5 peak exposures, while visiting industrial locations may increase them in and around pregnancy.